Using genetic algorithms in a large nationally representative American sample to abbreviate the Multidimensional Experiential Avoidance Questionnaire

Using genetic algorithms in a large nationally representative American sample to abbreviate the Multidimensional Experiential Avoidance Questionnaire

Genetic algorithms (GAs) are robust machine learning approaches for abbreviating a large set of variables into a shorter subset that maximally captures the variance in the original data. We employed a GA-based method to shorten the 62-item Multidimensional Experiential Avoidance Questionnaire (MEAQ)...

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Bibliographic Details
Main Authors: Baljinder Kaur Sahdra, Joseph eCiarrochi, Philip eParker, Luca eScrucca
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-02-01
Series:Frontiers in Psychology
Subjects:
genetic algorithms
Measurement
experiential avoidance
Psychometrics.
Abbreviation
Online Access:http://journal.frontiersin.org/Journal/10.3389/fpsyg.2016.00189/full

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